With the present security concerns in the world, there is a heightened need for systems and methods that can recognize or identify individuals in various settings. For example, security needs often dictate that an individual be correctly identified before the individual is permitted to perform some task, such as using an automated teller machine (ATM) or entering an airplane, a federal or state facility, an airport location, or other restricted area.
Traditional methods of identifying individuals, such as looking up a suspect in a book of mug shots, are slow, tedious, and prone to human error. For example, during the “look-up” phase, when a security officer attempts to match the face of a suspect to a depository of photographs of wanted criminals, there is the risk that a photograph of a wanted individual is overlooked in error. Additionally, in a setting where a large number of people are present, there is always the risk that a wanted criminal might get lost in the crowd, thus avoiding detection by security personnel.
Other traditional means of identification include signature or fingerprint identification, or presentation of an identification document, such as a passport or license. While useful in many circumstances, such methods, however, suffer from being intrusive because they require individuals to perform some act like signing or staining their thumb, or showing a document. Aside from the inconvenience of having to perform these acts, another drawback of such identification methods is that it gives the individual an opportunity to thwart the method by, for example, forging a signature or a passport.
To overcome some of the aforementioned limitations, systems and methods have been developed that can automatically recognize an individual. By employing such an automated system, security personnel are freed from having to perform this task using traditional slow and tedious methods. Automated methods, which rely on computers for recognition of individuals, can be both fast and accurate, and are therefore in high demand.
One automated method for recognizing an individual involves matching a facial image of the individual to a reference image from a database. For example, by using a camera to obtain the facial image of the individual, and then comparing selected pixel intensities of the facial image to those of reference images from the database, it is possible to determine if the facial image matches one from the database. If the matched reference individual can be associated with a name or some other identifier, then identification is possible.
Despite the advantages of the automated method, various factors can effect the quality of the facial image of the individual. For example, a common problem, especially for individuals who wear glasses, is the effect of glare from the glasses during imaging of the individual. If the resulting facial image is poor due to glare, subsequent identify of the individual from the facial image becomes significantly burdensome. Therefore, methods that can improve the accuracy of recognition systems, by improving the quality of the images acquired, would be most welcome.